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path: root/src/runtime/CL/functions/CLConvolutionLayer.cpp
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Diffstat (limited to 'src/runtime/CL/functions/CLConvolutionLayer.cpp')
-rw-r--r--src/runtime/CL/functions/CLConvolutionLayer.cpp102
1 files changed, 70 insertions, 32 deletions
diff --git a/src/runtime/CL/functions/CLConvolutionLayer.cpp b/src/runtime/CL/functions/CLConvolutionLayer.cpp
index f3c05adb47..7767b45a01 100644
--- a/src/runtime/CL/functions/CLConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLConvolutionLayer.cpp
@@ -28,11 +28,11 @@
#include "arm_compute/core/KernelDescriptors.h"
#include "arm_compute/core/utils/misc/ShapeCalculator.h"
#include "arm_compute/runtime/CL/functions/CLFFTConvolutionLayer.h"
+
+#include "src/common/utils/Log.h"
#include "src/core/CL/ICLKernel.h"
#include "src/core/helpers/MemoryHelpers.h"
#include "src/gpu/cl/operators/ClConv2d.h"
-
-#include "src/common/utils/Log.h"
#include "support/Cast.h"
namespace arm_compute
@@ -43,41 +43,59 @@ struct CLConvolutionLayer::Impl
{
MemoryGroup memory_group{};
std::shared_ptr<IMemoryManager> memory_manager{};
- std::unique_ptr<opencl::IClOperator> op{ nullptr };
+ std::unique_ptr<opencl::IClOperator> op{nullptr};
ITensorPack run_pack{};
ITensorPack prep_pack{};
WorkspaceData<CLTensor> workspace{};
experimental::MemoryRequirements aux_mem_req{};
- std::unique_ptr<IFunction> func{ nullptr };
+ std::unique_ptr<IFunction> func{nullptr};
};
-CLConvolutionLayer::CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager)
- : _impl(std::make_unique<Impl>())
+CLConvolutionLayer::CLConvolutionLayer(std::shared_ptr<IMemoryManager> memory_manager) : _impl(std::make_unique<Impl>())
{
_impl->memory_manager = std::move(memory_manager);
}
CLConvolutionLayer::~CLConvolutionLayer() = default;
-void CLConvolutionLayer::configure(ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info, const WeightsInfo &weights_info,
- const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups)
+void CLConvolutionLayer::configure(ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *biases,
+ ICLTensor *output,
+ const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info,
+ const Size2D &dilation,
+ const ActivationLayerInfo &act_info,
+ bool enable_fast_math,
+ unsigned int num_groups)
{
- configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups);
+ configure(CLKernelLibrary::get().get_compile_context(), input, weights, biases, output, conv_info, weights_info,
+ dilation, act_info, enable_fast_math, num_groups);
}
-void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLTensor *input, const ICLTensor *weights, const ICLTensor *biases, ICLTensor *output, const PadStrideInfo &conv_info,
- const WeightsInfo &weights_info,
- const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups)
+void CLConvolutionLayer::configure(const CLCompileContext &compile_context,
+ ICLTensor *input,
+ const ICLTensor *weights,
+ const ICLTensor *biases,
+ ICLTensor *output,
+ const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info,
+ const Size2D &dilation,
+ const ActivationLayerInfo &act_info,
+ bool enable_fast_math,
+ unsigned int num_groups)
{
ARM_COMPUTE_ERROR_ON_NULLPTR(input, weights, output);
- ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info, weights_info, dilation, act_info,
- enable_fast_math, num_groups));
- ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, weights_info, dilation, act_info, enable_fast_math, num_groups);
+ ARM_COMPUTE_ERROR_THROW_ON(CLConvolutionLayer::validate(
+ input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv_info,
+ weights_info, dilation, act_info, enable_fast_math, num_groups));
+ ARM_COMPUTE_LOG_PARAMS(input, weights, biases, output, conv_info, weights_info, dilation, act_info,
+ enable_fast_math, num_groups);
const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups);
- switch(opencl::ClConv2d::get_convolution_method(input->info(), weights->info(), output->info(), conv2d_info,
- weights_info, CLScheduler::get().target()))
+ switch (opencl::ClConv2d::get_convolution_method(input->info(), weights->info(), output->info(), conv2d_info,
+ weights_info, CLScheduler::get().target()))
{
case ConvolutionMethod::WINOGRAD:
case ConvolutionMethod::DIRECT:
@@ -85,7 +103,8 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT
case ConvolutionMethod::GEMM:
{
auto f = std::make_unique<opencl::ClConv2d>();
- f->configure(compile_context, input->info(), weights->info(), ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv2d_info, weights_info);
+ f->configure(compile_context, input->info(), weights->info(),
+ ((biases != nullptr) ? biases->info() : nullptr), output->info(), conv2d_info, weights_info);
_impl->op = std::move(f);
break;
}
@@ -101,40 +120,52 @@ void CLConvolutionLayer::configure(const CLCompileContext &compile_context, ICLT
break;
}
- if(_impl->op)
+ if (_impl->op)
{
_impl->memory_group = MemoryGroup(std::move(_impl->memory_manager));
_impl->aux_mem_req = _impl->op->workspace();
- _impl->run_pack = { { ACL_SRC_0, input }, { ACL_SRC_1, weights }, { ACL_SRC_2, biases }, { ACL_DST, output } };
- _impl->prep_pack = { { ACL_SRC_1, weights }, { ACL_SRC_2, biases } };
- _impl->workspace = manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
+ _impl->run_pack = {{ACL_SRC_0, input}, {ACL_SRC_1, weights}, {ACL_SRC_2, biases}, {ACL_DST, output}};
+ _impl->prep_pack = {{ACL_SRC_1, weights}, {ACL_SRC_2, biases}};
+ _impl->workspace =
+ manage_workspace<CLTensor>(_impl->aux_mem_req, _impl->memory_group, _impl->run_pack, _impl->prep_pack);
}
}
-Status CLConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output, const PadStrideInfo &conv_info,
- const WeightsInfo &weights_info, const Size2D &dilation, const ActivationLayerInfo &act_info, bool enable_fast_math, unsigned int num_groups)
+Status CLConvolutionLayer::validate(const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *biases,
+ const ITensorInfo *output,
+ const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info,
+ const Size2D &dilation,
+ const ActivationLayerInfo &act_info,
+ bool enable_fast_math,
+ unsigned int num_groups)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, weights, output);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(!weights->are_values_constant(), "Dynamic weights are not supported");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((num_groups != 1) && (input->data_layout() != DataLayout::NCHW), "Grouping (num_groups != 1) with NHWC data layout is not supported");
+ ARM_COMPUTE_RETURN_ERROR_ON_MSG((num_groups != 1) && (input->data_layout() != DataLayout::NCHW),
+ "Grouping (num_groups != 1) with NHWC data layout is not supported");
const GPUTarget gpu_target = CLScheduler::get().target();
const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, num_groups);
- switch(opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target))
+ switch (opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target))
{
case ConvolutionMethod::WINOGRAD:
case ConvolutionMethod::DIRECT:
case ConvolutionMethod::INDIRECT:
case ConvolutionMethod::GEMM:
{
- ARM_COMPUTE_RETURN_ON_ERROR(opencl::ClConv2d::validate(input, weights, biases, output, conv2d_info, weights_info));
+ ARM_COMPUTE_RETURN_ON_ERROR(
+ opencl::ClConv2d::validate(input, weights, biases, output, conv2d_info, weights_info));
break;
}
case ConvolutionMethod::FFT:
{
// Validate FFT-based convolution layer
- ARM_COMPUTE_RETURN_ON_ERROR(CLFFTConvolutionLayer::validate(input, weights, nullptr, output, conv_info, act_info, enable_fast_math));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLFFTConvolutionLayer::validate(input, weights, nullptr, output, conv_info,
+ act_info, enable_fast_math));
break;
}
default:
@@ -145,8 +176,15 @@ Status CLConvolutionLayer::validate(const ITensorInfo *input, const ITensorInfo
return Status{};
}
-ConvolutionMethod CLConvolutionLayer::get_convolution_method(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *output, const PadStrideInfo &conv_info,
- const WeightsInfo &weights_info, const ActivationLayerInfo &act_info, const GPUTarget gpu_target, const Size2D &dilation, bool enable_fast_math)
+ConvolutionMethod CLConvolutionLayer::get_convolution_method(const ITensorInfo *input,
+ const ITensorInfo *weights,
+ const ITensorInfo *output,
+ const PadStrideInfo &conv_info,
+ const WeightsInfo &weights_info,
+ const ActivationLayerInfo &act_info,
+ const GPUTarget gpu_target,
+ const Size2D &dilation,
+ bool enable_fast_math)
{
const Conv2dInfo conv2d_info = Conv2dInfo(conv_info, dilation, act_info, enable_fast_math, 1);
return opencl::ClConv2d::get_convolution_method(input, weights, output, conv2d_info, weights_info, gpu_target);
@@ -158,7 +196,7 @@ void CLConvolutionLayer::run()
MemoryGroupResourceScope scope_mg(_impl->memory_group);
- if(_impl->func)
+ if (_impl->func)
{
_impl->func->run();
}
@@ -170,7 +208,7 @@ void CLConvolutionLayer::run()
void CLConvolutionLayer::prepare()
{
- if(_impl->func)
+ if (_impl->func)
{
_impl->func->prepare();
}
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-19 22:16:51 +0000